Dynamic neural networks for temporal feature alignment in asynchronous multi-sensor fusion systems

A method comprising:

• receiving, at processing circuitry, first frames from a first sensor;
• receiving, at the processing circuitry, second frames from a second sensor;
• performing a first feature extraction on the first frames using a first dynamic neural network to determine first features;
• performing a second feature extraction on the second frames using a second dynamic neural network to determine second features;
• determining a first delay associated with the first features;
• determining a second delay associated with the second features;
• modifying a topology of the second dynamic neural network based on the first delay and the second delay;
• and
• using the second dynamic neural network with the modified topology to generate an output.

A computer-readable storage medium storing instructions that when executed by one or more processors cause the one or more processors to:

• receive first frames from a first sensor;
• receive second frames from a second sensor;
• perform a first feature extraction on the first frames using a first dynamic neural network to determine first features;
• perform a second feature extraction on the second frames using a second dynamic neural network to determine second features;
• determine a first delay associated with the first features;
• determine a second delay associated with the second features;
• modify a topology of the second dynamic neural network based on the first delay and the second delay;
• and
• use the second dynamic neural network with the modified topology to generate an output.